def plot_max_mem_error(q):
blacklist = Utils.init_blacklist("config/mal_blacklist.txt")
col_stats = ColumnStatsD.fromFile('config/tpch_sf10_stats.txt')
for qno in q:
logging.info("Testing query {}".format(qno))
q = "{}".format(qno)
if qno < 10:
q = "0{}".format(q)
logging.info("loading training set...")
d1 = MalDictionary.fromJsonFile(
"traces/random_tpch_sf10/ran{}_200_sf10.json".format(qno),
blacklist, col_stats)
logging.info("loading test set...")
d2 = MalDictionary.fromJsonFile("traces/tpch-sf10/{}.json".format(q),
blacklist, col_stats)
train_tags = d1.query_tags
train_tags.sort()
e = []
ind = []
for i in [
1, 5, 10, 15, 20, 25, 30, 40, 50, 75, 100, 125, 150, 175, 200
]:
d12 = d1.filter(lambda ins: ins.tag in train_tags[0:i])
print(len(d12.query_tags))
pG = d2.buildApproxGraph(d12)
pmm = d2.predictMaxMem(pG) / 1000000000
mm = d2.getMaxMem() / 1000000000
e.append(100 * abs((pmm - mm) / mm))
ind.append(i)
print(e)
Utils.plotBar(ind, e, "results/memf_error_q{}.pdf".format(qno),
'nof training queries', 'error perc')
def plot_allmem_tpch10(path=""):
blacklist = Utils.init_blacklist("config/mal_blacklist.txt")
col_stats = ColumnStatsD.fromFile('config/tpch_sf10_stats.txt')
e = []
for qno in range(1, 23):
q = "0{}".format(qno) if qno < 10 else "{}".format(qno)
logging.info("Examining Query: {}".format(q))
d1 = MalDictionary.fromJsonFile(
"traces/random_tpch10/ran_q{}_n200_tpch10.json".format(q),
blacklist, col_stats)
d2 = MalDictionary.fromJsonFile("traces/tpch10/{}.json".format(q),
blacklist, col_stats)
pG = d2.buildApproxGraph(d1)
pmm = d2.predictMaxMem(pG) / 1_000_000_000
mm = d2.getMaxMem() / 1_000_000_000
err = 100 * abs((pmm - mm) / mm)
print("query: {}, pred mem: {}, actual mem: {}, error {}".format(
qno, pmm, mm, err))
e.append(err)
print(err)
# TODO: use os.path.join for the following
outf = path + "mem_error_1-23.pdf"
Utils.plotBar(range(1, 23), e, outf, 'error perc', 'query no')